Wednesday, November 30, 2016

Ashley Coates asks some of the lucky few that have tried the 1972 release from Balvenie

The Balvenie DCS Compendium Chapter II

They stare down at you from glass cabinets in
London’s high-end retailers, seemingly untouchable. But what does a
whisky in this category actually taste like, and how does it get to be
so expensive?

To
answer these questions, I looked to some of the experts in the
business, all of which have been given the chance to sample the recently
released 1972 Balvenie from the DCS Compendium Chapter II.

Balvenie
does not specialise in ultra-rare whiskies. The Speyside distillery
offers some comparatively reasonably priced and popular variations, the
12-Year Doublewood, the 14-year Caribbean Cask and the 17-Year
Doublewood being amongst the best known and most appreciated.

But this year was a special one for Balvenie. It’s
the 53rd year in which its Malt Master, David Charles Stewart MBE, has
been creating world-famous whiskies for the firm. Having been appointed
Master Distiller to Balvenie back in 1974, he’s the longest serving
master distiller in the whisky industry. The DCS Compendium has been
made to honour 50 years in the business and is an “unconventional
handover note” from David, who said at the time of the release: “I had
to leaf through ledgers, search computer records, and had to hop, quite
literally, barrel over barrel to seek them out in the various
warehouses”. There will be five 'chapters' in the compendium, each
consisting of five rare whiskies, released over five years....MUCH MORE

The precedent is already established, the one used in "Reply of the Zaporozhian Cossacks", see below.

The problem with what Erdoğan is doing is it risks drawing NATO into a war with Syria and their ally Russia.
From al-Monitor:

A top Russian diplomat rebuked Turkey’s president over his comments on
Syria today, saying they contradict international agreements on the
war-wracked country. Russian Deputy Foreign Minister Mikhail Bogdanov
told Russian news agencies Nov. 30 that his government was puzzled by
Recep Tayyip Erdogan’s assertion a day earlier that Turkey was in Syria for no reason other than to topple President Bashar al-Assad. "We are there to bring justice. We are there to end the rule of the cruel Assad, who has been spreading state terror," Erdogan said.

His words flew in the face of Turkey’s earlier claims that it had sent its troops into northern Syria
to battle the Islamic State and the Syrian Kurdish militia known as the
People’s Protection Units: It's against all international agreements
that Turkey is party to “if Erdogan plans to wage war,” on Assad,
Bogdanov said.

In separate remarks, Kremlin spokesman Dmitry Peskov told reporters, "It is a very serious statement and
one which differs from previous ones and with our understanding of the
situation. We hope that our Turkish partners will provide us with some
kind of explanation about this."
There has not been any yet.

Russia and Iran are the Syrian regime's chief allies in the war
against opposition rebels who are, in turn, supported by Turkey, various
Gulf states and in part by the CIA. But in recent months Turkey has
signaled willingness to rein in the one group that poses the biggest
threat to Assad’s rule — the al-Qaeda-linked Jabhat al-Nusra, which now
calls itself Jabhat Fatah al-Sham. The shift followed a frenzied
campaign by Turkey to woo back Russia after the pair fell out over Turkey’s downing of a Russian jet in November last year.

Analysts reckon Erdogan’s latest spate of hawkishness has more to do
with placating his own Islamist base than with yet another U-turn in
Turkey’s thus far disastrous Syria policy....MORE

Private
equity firms have largely stayed away from agriculture due to the risks
the sector presents, said David Gray, partner at Altima Partners, an
investment manager.

"PE firms don't like commodity risk," said Mr Gray.

Such
investors had tended to shy away from the production side of the
agriculture sector and focus instead on "value add" – that is, the
industries processing raw farm commodities into higher value products.

"There
is too much uncertainty involving weather and crop," said Mr Gray at the
AgriRisk Forum in London. "They don't know what the weather is going to
be like or what the production figures will be."...MORE

A couple years ago one private equity fund, ACM was raising $250 million but I don't know if it has deployed all the money. The last time I looked they were growing organic blueberries and hazelnuts but on the one hand if you put that much loot into blueberries you'd probably have antitrust problems and on the other, the international hazelnut cartel is facing declines in the Gin Gimlet end-market and Nutella is getting vertically integrated in their sourcing.

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Yves here. By virtue of steamrolling local taxi operations in cities
all over the world, combined with cultivating cheerleaders in the
business press and among Silicon Valley libertarians, Uber has managed
to create an image of inevitability and invincibility. How much is hype
and how much is real?

As transportation industry expert Hubert Horan will demonstrate in
his four-part series, Uber has greatly oversold its case. There are no
grounds for believing that Uber will ever be profitable, let alone
justify its lofty valuation, absent perhaps the widespread
implementation of driverless cars. Lambert has started digging into that
issue, and his posts on that topic have consistently found that the
technology would be vastly more difficult to develop and implement that
its boosters acknowledge, would require substantial upgrading in roads,
may never be viable in adverse weather conditions (snow and rain) and is
least likely to be implemented in cities, which present far more
daunting design demands that long-distance transport on highways.

By Hubert Horan, who has 40 years of experience in the
management and regulation of transportation companies (primarily
airlines). Horan has no financial links with any urban car service
industry competitors, investors or regulators, or any firms that work on
behalf of industry participants.

Uber is currently the most highly valued private company in the
world. Its primarily Silicon Valley-based investors have a achieved a
venture capital valuation of $69 billion based on direct investment of
over $13 billion. Uber hopes to earn billions in returns for those
investors out of an urban car service industry that historically had
razor-thin margins producing a commodity product. Although the industry
has been competitively fragmented and structurally stable for over a
century, Uber has been aggressively pursuing global industry dominance,
in the belief that the industry has been radically transformed into a
“winner-take-all” market.

This is the first of a series of articles addressing the question of
whether Uber’s pursuit of global industry dominance would actually
improve the efficiency of the urban car service industry and improve
overall economic welfare.

For Uber (or any other radical industry restructuring) to be welfare enhancing, it would have to clearly demonstrate:

The ability to earn sustainable profits in competitive
markets large enough to provide attractive returns on its invested
capital

The ability to provide service at significantly lower cost, or the
ability to produce much higher quality service at similar costs

That it has created new sources of sustainable competitive advantages
through major product redesigns and technology/process innovations that
incumbent producers could not readily match, and

Evidence that the newly-dominant company will have strong incentive
to pass on a significant share of those efficiency gains to consumers.

Unlike most startups, Uber did not enter the industry in pursuit of a
significant market share, but was explicitly working to drive
incumbents out of business and achieve global industry dominance. Uber’s
huge valuation was always predicated on the dramatic growth towards
global dominance. Thus if Uber’s valuation and industry dominance were
to be welfare enhancing, Uber’s efficiency and competitive advantages
would need to be overwhelming, and there would need to be clear evidence
of Uber’s ability to generate large profits and consumer welfare
benefits out of these advantages.

While most media coverage focused on isolated Uber product
attributes, or its corporate style and image, this series will focus on
the overall economics of Uber, using the approaches that outsiders
examining industry competitive dynamics or investment opportunities
typically would. This first article will present evidence on Uber’s
profitability, while subsequent pieces will present evidence about cost
efficiency, competitive advantage and the other issues critical to the
larger economic welfare question.

Uber Has Operating Losses of $2 Billion a Year, More Than Any Startup in History
Published financial data shows that Uber is losing more money than
any startup in history and that its ability to capture customers and
drivers from incumbent operators is entirely due to $2 billion in annual
investor subsidies. The vast majority of media coverage presumes Uber
is following the path of prominent digitally-based startups whose large
initial losses transformed into strong profits within a few years.

This presumption is contradicted by Uber’s actual financial results,
which show no meaningful margin improvement through 2015 while the
limited margin improvements achieved in 2016 can be entirely explained
by Uber-imposed cutbacks to driver compensation. It is also contradicted
by the fact that Uber lacks the major scale and network economies that
allowed digitally-based startups to achieve rapid margin improvement.

As a private company, Uber is not required to publish financial
statements, and financial statements disseminated privately are not
required to be audited in accordance with generally accepted accounting
principles (GAAP) or satisfy the SEC’s reporting standards for public
companies.

The financial tables below are based on private financial statements
that Uber shared with investors that were published in the financial
press on three separate occasions. The first set included data for 2012,
2013 and the first half of 2014, although only EBITAR (before interest,
taxes, depreciation and amortization) contribution was shown, not the
true (GAAP) profit that publically traded companies report.[1] The second set included tables of GAAP profit data for full year 2014 and the first half of 2015;[2] the third set included summary EBITAR contribution data for the first half of 2016.[3] There has been no public report of results for the fourth quarter of 2015.

Exhibit 1 summarizes data from 2013 through the first half of 2015.
Drivers retained 83% of passenger payments (fares plus tips) which must
cover the cost of vehicle ownership, insurance and maintenance, fuel,
credit card and license fees as well as health insurance and take home
pay; the balance is Uber’s total revenue. Exhibit 2 shows the GAAP
results for the full year ending September 2015 based on the published
numbers and an estimated quarterly split of published 2nd half 2014
results. Exhibit 3 compares first half 2016 results to 2014-15 results.
There is no simple relationship between EBITAR contribution and GAAP
profitability and even publically traded companies have wide leeway as
to what expenses can be excluded from interim contribution measures such
as EBITAR.

As shown in Exhibit 2, for the year ending September 2015, Uber had
GAAP losses of $2 billion on revenue of $1.4 billion, a negative 143%
profit margin. Thus Uber’s current operations depend on $2 billion in
subsidies, funded out of the $13 billion in cash its investors have
provided.
Uber passengers were paying only 41% of the actual cost of their
trips; Uber was using these massive subsidies to undercut the fares and
provide more capacity than the competitors who had to cover 100% of
their costs out of passenger fares.

Many other tech startups lost money as they pursued growth and market
share, but losses of this magnitude are unprecedented; in its
worst-ever four quarters, in 2000, Amazon had a negative 50% margin,
losing $1.4 billion on $2.8 billion in revenue, and the company
responded by firing more than 15 percent of its workforce.[4] 2015 was Uber’s fifth year of operations; at that point in its history Facebook was achieving 25% profit margins.[5]

No Evidence of the Rapid Margin Improvement That Drove Other Tech Startups to Profitability
There is no evidence that Uber’s rapid growth is driving the rapid
margin improvements achieved by other prominent tech startups as they
“grew into profitability.”...

The 'Washington Post' 'Blacklist' Story Is Shameful and DisgustingThe capital's paper of record crashes legacy media on an iceberg

Last week, a technology reporter for the Washington Post named
Craig Timberg ran an incredible story. It has no analog that I can think
of in modern times. Headlined "Russian propaganda effort helped spread
'fake news' during election, experts say," the piece
promotes the work of a shadowy group that smears some 200 alternative
news outlets as either knowing or unwitting agents of a foreign power,
including popular sites like Truthdig and Naked Capitalism.

The thrust of Timberg's astonishingly lazy report is that a Russian
intelligence operation of some kind was behind the publication of a
"hurricane" of false news reports during the election season, in
particular stories harmful to Hillary Clinton. The piece referenced
those 200 websites as "routine peddlers of Russian propaganda."

The
piece relied on what it claimed were "two teams of independent
researchers," but the citing of a report by the longtime anticommunist
Foreign Policy Research Institute was really window dressing.

The meat of the story relied on a report by unnamed analysts from a single mysterious "organization" called PropOrNot
– we don't know if it's one person or, as it claims, over 30 – a
"group" that seems to have been in existence for just a few months.

It was PropOrNot's report that identified what it calls "the list"
of 200 offending sites. Outlets as diverse as AntiWar.com,
LewRockwell.com and the Ron Paul Institute were described as either
knowingly directed by Russian intelligence, or "useful idiots" who
unwittingly did the bidding of foreign masters.

Forget that the Post
offered no information about the "PropOrNot" group beyond that they
were "a collection of researchers with foreign policy, military and
technology backgrounds."...MORE

...“There is a certain
profound lack of empathy,” he said,
“in asserting that the only reason why someone could have voted the way
they did is because they saw some fake news. If you believe that, then I
don’t think you have internalized the message that Trump supporters are
trying to send in this election.” When asked to articulate that
message, he dodged the question.

“Empathy”
is one of Facebook’s all-time favorite buzzwords. For years, Zuckerberg
has hopped from conference to conference in a selection of muted
hoodies and T-shirts, delivering variations on the same pitch. “More
people are using Facebook to share more stuff,” he said in 2010. “That
means that if we want, there’s more out there that we can go look at and
research and understand what’s going on with the people around us. And I
just think that leads to broader empathy, understanding — just a lot of
good, core, human things that make society function better.”...

Closer to where Ms. Kaminska is getting to, but still coming in on a tangent is Om Malik's New Yorker piece, but here, you be the judge.
Picking up where we left off with the Alphaville post yesterday:

...And yet, what is being lost in the midst of all this outrage, is that there’s an entity being born out there which stands to be far more discriminatory, bull-headed and fascist
than any human being could ever be. That entity is “artificial
intelligence”. Thus far, the entire quant/data-first movement which
supports and feeds it, by actively celebrating the removal of feelings
from the evaluation equation, seems entirely oblivious to that fact.

Yet, what we’re discovering through the AI big data phenomenon, isn’t just that algorithms discriminate on a continuous basis,
it’s that they make terrible assumptions about the human condition when
they do so. Without the ability to empathise or respect a human’s
capacity to change, better himself or hold contradictory view points at
the same time, algorithms crunch data for patterns and correlations and
interpret them to assume x, y or z is a defaulter or a criminal just
because that’s what the data probabilities for his group-type or
associations suggest.

All in all, this is why discrimination is
the single biggest problem facing the artificial intelligence field.
It’s all the more imposing, we’d add, in sectors where AI and big data
is being used to assess or reduce risk, such as insurance.
If you smoke, live in a dodgy area and have a penchant for chocolate or
wine, you might become uninsurable. Nor does the big data solutionist
mindset address the fact that the rich, who can afford to pay the
premiums, can get away with the wrong behaviours for as long as they
have the money to fund the privileges.

And since algos can’t judge
exceptions, or be appealed to in exceptional circumstance without the
intervention of a costly human go-between, the only work-around is for
the discriminated to agree to an extended period of extreme surveillance
and restricted freedom....MORE

Silicon Valley
seems to have lost a bit of its verve since the Presidential election.
The streets of San Francisco—spiritually part of the Valley—feel less
crowded. Coffee-shop conversations are hushed. Everything feels a little
muted, an eerie quiet broken by chants of protesters. It even seems as
if there are more parking spots. Technology leaders, their employees,
and those who make up the entire technology ecosystem seem to have been
shaken up and shocked by the election of Donald Trump.

One
conversation has centered on a rather simplistic narrative of Trump as
an enemy of Silicon Valley; this goes along with a self-flagellating
regret that the technology industry didn’t do enough to get Hillary
Clinton into the White House. Others have decided that the real villains
are Silicon Valley giants, especially Twitter, Facebook, and Google,
for spreading fake news stories that vilified Clinton and helped elect
an unpopular President.

These
charges don’t come as a surprise to me. Silicon Valley’s biggest
failing is not poor marketing of its products, or follow-through on
promises, but, rather, the distinct lack of empathy for those whose
lives are disturbed by its technological wizardry. Two years ago, on my
blog, I wrote,
“It is important for us to talk about the societal impact of what
Google is doing or what Facebook can do with all the data. If it can
influence emotions (for increased engagements), can it compromise the
political process?”

Perhaps
it is time for those of us who populate the technology sphere to ask
ourselves some really hard questions. Let’s start with this: Why did so
many people vote for Donald Trump? Glenn Greenwald, the firebrand
investigative journalist writing for The Intercept, and the documentary filmmaker Michael Moore have
listed many reasons Clinton lost. Like Brexit, the election of Donald
Trump has focussed attention on the sense that globalization has eroded
the real prospects and hopes of the working class in this country.
Globalization is a proxy for technology-powered capitalism, which tends
to reward fewer and fewer members of society.

My
hope is that we in the technology industry will look up from our
smartphones and try to understand the impact of whiplashing change on a
generation of our fellow-citizens who feel hopeless and left behind.
Instead, I read the comments of Balaji Srinivasan, the C.E.O. of the San
Francisco-based Bitcoin startup 21 Inc., telling the Wall Street Journal columnist Christopher Mims
that he feels more connected to people in his “Stanford network” around
the globe than to those in California’s Central Valley: “There will be a
recognition that if we don’t have control of the nation state, we
should reduce the nation state’s power over us.”

It’s
hard to think about the human consequences of technology as a founder
of a startup racing to prove itself or as a chief executive who is
worried about achieving the incessant growth that keeps investors happy.
Against the immediate numerical pressures of increasing users and
sales, and the corporate pressures of hiring the right (but not too
expensive) employees to execute your vision, the displacement of people
you don’t know can get lost.

However,
when you are a data-driven oligarchy like Facebook, Google, Amazon, or
Uber, you can’t really wash your hands of the impact of your algorithms
and your ability to shape popular sentiment in our society. We are not
just talking about the ability to influence voters with fake news. If
you are Amazon, you have to acknowledge that you are slowly corroding
the retail sector, which employs many people in this country. If you are
Airbnb, no matter how well-meaning your focus on delighting travellers,
you are also going to affect hotel-industry employment.

Otto, a Bay Area startup that was recently acquired by Uber, wants to automate trucking—and recently wrapped up
a hundred-and-twenty-mile driverless delivery of fifty thousand cans of
beer between Fort Collins and Colorado Springs. From a technological
standpoint it was a jaw-dropping achievement, accompanied by predictions
of improved highway safety. From the point of view of a truck driver
with a mortgage and a kid in college, it was a devastating “oh, shit”
moment. ...MORE

...To
many in Silicon Valley, this is just part of inexorable progress.
Electing Mr. Trump won’t shield his supporters from the reality that
they are now competing with every other worker on Earth, says Balaji
Srinivasan, a board partner at venture-capital firm Andreessen Horowitz
and CEO of bitcoin startup 21 Inc.

Mr.
Srinivasan views the collision between tech culture and Mr. Trump’s
populist movement as inevitable, and potentially so divisive that tech’s
global elites should effectively secede from their respective countries, an idea he calls “the ultimate exit.”

Already,
he says, elites in Silicon Valley are more connected to one another and
to their counterparts around the globe than to non-techies in their
midst or nearby. “My Stanford network connects to Harvard and Beijing
more than [California’s] Central Valley,” says Mr. Srinivasan.
Eventually, he argues, “there will be a recognition that if we don’t
have control of the nation state, we should reduce the nation state’s
power over us.”...

As the presidential election frenzy enters
its post-election lull, let’s take a moment to visit one of the most
controversial periods in election history and the impact that it had on
October’s media publications ranking.

The
recent election period saw a general awakening of politically heavy
news sites; the first signs of change were visible already few months
prior to the election. Take the publication fivethirtyeight.com, which was ranked at a mere 106 in June 2016. Over the last few months, it jumped 93 positions, reaching 13th place in October and was flanked by prominent domains like washingtonpost.com and businessinsider.com.

Keyword Contenders

Another indication of fivethirtyeight.com’s progress can be seen in the graph below
which displays the top sites contending for the keyword “election” from
May 2016 – Oct. 2016. Fivethirtyeight.com showed the highest increase
in its share of the search term, sparring against cnn.com, nytimes.com,
bbc.com and the washingtonpost.com.....

Aberdeen‘s full-year
results make for bleak reading. The group grew assets under management
to 312.1 billion pounds, but this was flattered by the weaker level of
sterling, and acquisitions. Net flows were negative. Despite the higher
assets, revenue and pre-tax profit sank 14 and 28 percent respectively,
as fee margins fell.

Aberdeen‘s challenges are individual and
sector-wide. Its emerging market franchise has been pumped up by years
of loose U.S. monetary policy, and now faces a stronger dollar as the
Federal Reserve raises rates. U.S. President-elect Donald Trump wants to
bring back domestic jobs from emerging economies, and may trigger trade
wars. Trump may be all talk, but competition from cheaper passive and
“smart beta” funds is not. Finally, regulators are demanding managers
hold more capital and are scrutinising competition.

Aberdeen has strengths. Its emerging
markets business may be more resilient to the passive onslaught than
managers focused on more commoditised developed market equities. And its
blended margin of 30 basis points is already lower than many peers’....MORE

Hebrew University of Jerusalem - Jerusalem School of Business Administration

September 11, 2016

Abstract:

The most popular portfolio performance measures are
the Sharpe ratio and alpha. While the Sharpe ratio is optimal under the
CAPM assumptions of normal return distributions and unlimited borrowing
at the risk-free rate, we find that it is not well aligned with
investors’ preferences in more realistic settings. Alpha is a poor
measure under both the theoretical and the realistic settings. For
investors with typical borrowing constraints, the geometric mean
provides an alternative measure that is much better than both the Sharpe
ratio and alpha. It may very well be the most important single number
to consider in portfolio selection.

Last week, DE (UW) posted an upside FQ4’16 report and introduced FY’17
guidance above consensus; the stock is up 11% since the report vs.
S&P 500 flat. We wanted to circle back with management before
publishing our model update as we had a number of outstanding questions
around the guidance. Management introduced its FY’17 outlook for net
income of $1.4B (implied ~$4.42 EPS vs. prior consensus $3.84) on
equipment sales down 1%...

A post by Izabella Kaminska at FT Alphaville earlier today reminded me of a piece at Quanta I'd meant to link.
I'll be coming back to the Alphaville riff tomorrow, there are just so many ideas popping out of it I can't do it during the work day. Here's one example in the first three paragraphs:

Conversations across the political spectrum are exploding into
emotionally charged and heated rampages — many of them focused on
calling out x, y or z as bigoted, racist or discriminatory.

Deeming
x, y or z as either or the other is beyond the scope or remit of this
blog. What we’re concerned with is how this fits into the fake news
paradigm and why it ultimately jars with the sacred notion that people
are supposed to be presumed innocent until proven guilty — and that
guilt should be determined through a fair evaluation of actions
rather than words. This practice is a hallowed facet of liberal
representative democracy because once someone is accused of holding an
unpopular view, it’s often impossible to wage a convincing defence
outside of this formal process.

Proving a negative is largely
futile. Proving you don’t secretly think x, y or z, meanwhile, is nigh
on impossible unless you support a hitherto only seen in sci-fi
literature scale of personal intrusion (thought police,
ahem), undermining not just the sanctity of the privacy of one’s mind
but also the scope and feel of what it means to be an individual....

Well, what she's pointing out is such a threat to representative government that Machiavelli in his discourses on the first ten books of Livy's history of the Roman Republic mentions calumny (The making of false and defamatory statements about someone in order to damage their reputation; slander...O.E.D.) at least a hundred times and in fact dedicates a chapter (XIII of book I) to making the distinction between accusation as a tool for finding the truth and calumny as a method of destruction:

As you can see, we haven't even gotten past the intro, much less mentioned algos, and we're already off into some seriously important stuff and so, by your leave, I'll do some cut-and-paste from Quanta, who in any event are smarter than I by orders of magnitude and come back to Algo Discrimination mañana.From Quanta Magazine, Nov. 23:

How to Force Our Machines to Play FairThe computer scientist Cynthia Dwork takes abstract concepts like
privacy and fairness and adapts them into machine code for the
algorithmic age.

Theoretical computer science can be as remote and abstract as pure
mathematics, but new research often begins in response to concrete,
real-world problems. Such is the case with the work of Cynthia Dwork.

Over the course of a distinguished career, Dwork has crafted rigorous
solutions to dilemmas that crop up at the messy interface between
computing power and human activity. She is most famous for her invention
in the early to mid-2000s of “differential privacy,”
a set of techniques that safeguard the privacy of individuals in a
large database. Differential privacy ensures, for example, that a person
can contribute their genetic information to a medical database without
fear that anyone analyzing the database will be able to figure out which
genetic information is hers — or even whether she has participated in
the database at all. And it achieves this security guarantee in a way
that allows researchers to use the database to make new discoveries.

Dwork’s latest work has a similar flavor to it. In 2011 she became
interested in the question of fairness in algorithm design. As she
observes, algorithms increasingly control the kinds of experiences we
have: They determine the advertisements we see online, the loans we
qualify for, the colleges that students get into. Given this influence,
it’s important that algorithms classify people in ways that are
consistent with commonsense notions of fairness. We wouldn’t think it’s
ethical for a bank to offer one set of lending terms to minority
applicants and another to white applicants. But as recent work has shown
— most notably in the book “Weapons of Math Destruction,” by the mathematician Cathy O’Neil — discrimination that we reject in normal life can creep into algorithms.

Privacy and ethics are two questions with their roots in philosophy.
These days, they require a solution in computer science. Over the past
five years, Dwork, who is currently at Microsoft Research but will be
joining the faculty at Harvard University in January, has been working
to create a new field of research on algorithmic fairness. Earlier this
month she helped organize a workshop at Harvard that brought together
computer scientists, law professors and philosophers.

Quanta Magazine spoke with Dwork about algorithmic fairness,
her interest in working on problems with big social implications, and
how a childhood experience with music shaped the way she thinks about
algorithm design today. An edited and condensed version of the interview
follows.

QUANTA MAGAZINE: When did it become obvious to you that computer science was where you wanted to spend your time thinking?
CYNTHIA DWORK: I always enjoyed all of my subjects, including science
and math. I also really loved English and foreign languages and, well,
just about everything. I think that I applied to the engineering school
at Princeton a little on a lark. My recollection is that my mother said,
you know, this might be a nice combination of interests for you, and I
thought, she’s right.

It was a little bit of a lark, but on the other hand it seemed as
good a place to start as any. It was only in my junior year of college
when I first encountered automata theory that I realized that I might be
headed not for a programming job in industry but instead toward a Ph.D.
There was a definite exposure I had to certain material that I thought
was beautiful. I just really enjoyed the theory.

You’re best known for your work on differential privacy. What drew you to your present work on “fairness” in algorithms?
I wanted to find another problem. I just wanted something else to
think about, for variety. And I had enjoyed the sort of social mission
of the privacy work — the idea that we were addressing or attempting to
address a very real problem. So I wanted to find a new problem and I
wanted one that would have some social implications.

So why fairness?
I could see that it was going to be a major concern in real life.

How so?
I think it was pretty clear that algorithms were going to be used in a
way that could affect individuals’ options in life. We knew they were
being used to determine what kind of advertisements to show people. We
may not be used to thinking of ads as great determiners of our options
in life. But what people get exposed to has an impact on them. I also
expected that algorithms would be used for at least some kind of
screening in college admissions, as well as in determining who would be
given loans.

I didn’t foresee the extent to which they’d be used to screen
candidates for jobs and other important roles. So these things — what
kinds of credit options are available to you, what sort of job you might
get, what sort of schools you might get into, what things are shown to
you in your everyday life as you wander around on the internet — these
aren’t trivial concerns.

Your 2012 paper that launched this line of your research hinges on the concept of “awareness.” Why is this important?
One of the examples in the paper is: Suppose you had a minority group
in which the smart students were steered toward math and science, and a
dominant group in which the smart students were steered toward finance.
Now if someone wanted to write a quick-and-dirty classifier to find
smart students, maybe they should just look for students who study
finance because, after all, the majority is much bigger than the
minority, and so the classifier will be pretty accurate overall. The
problem is that not only is this unfair to the minority, but it also has
reduced utility compared to a classifier that understands that if
you’re a member of the minority and you study math, you should be viewed
as similar to a member of the majority who studies finance. That gave
rise to the title of the paper, “Fairness Through Awareness,” meaning cross-cultural awareness....MORE

U.S. dollar index up 0.24 at 101.63; euro down a fraction at 105.75.
From Marc to Market:

The US dollar correctly [sic]lowered
yesterday, but most of the selling was over by the end of the Asian session, and the greenback steadied in Europe
and North America. The dollar is firm against the euro and yen but within yesterday's broad trading
ranges. The Australian and Canadian dollar's gains from yesterday are being pared.

What had looked like a possible
deeper dollar correction is turning into a consolidative phase that may be
sufficient to alleviate the over-extended technical condition. Equities are
lower. Of note, the Topix 12-day advance was snapped with a minor loss of
less than 0.1%. The MSCI Asia-Pacific Index is off 0.25% to snap a
three-day advance. The Dow Jones Stoxx 600 is off fractionally to extend
yesterday's decline. The MSCI Emerging Market equity index is
lower by 0.25%, after initially building on yesterday's advance to reach a
two-week high. The South African rand is the weakest of majors, while
the Chinese yuan, which was fixed higher by the PBOC for the second session, is
the strongest of the emerging market currencies, gaining almost 0.3%.
European bonds firmer, led by a 6 bp decline in Italy's 10-year yield.
French bonds are also outperforming German bunds, narrowing the premium
from a two-year peak. The US 10-year yield is firm near 2.33%.

Sterling is an exception. It is firmer, following news that
mortgage approvals rose more than expected in October to stand at the highest
since March, while household credit increased GBP1.6 bln. The
Bank of England noted that the effective interest rate on new mortgages fell 11
bp in October to 2.16%, the lowest since at least 2004. However, even
with the upticks sterling has been
confined to yesterday's ranges....MORE

Dirty deeds, not dirt cheap.
It's pretty well established that the punishment for an agent's breach of the duty of loyalty to his principal is death.
At least in Russia at any rate

From Art Market Monitor:

Perhaps you’ve heard of this lawsuit where the dealers who bought a
$10,000 painting and sold it for $80m are upset that the buyer was
representing another buyer who sold it for almost $50m more?

Such is the trouble that Yves Bouvier’s dealings with Dmitry
Rybolovlev have caused. Bouvier, acting in the interest of Rybolovlev,
bought works of art that he then sold on to the Russian at huge markups.
The whole scheme fell apart a few winters ago in St. Barth’s when an
art advisor clued Rybolovlev in to the prices Bouvier was actually
paying.

The New York Times has a story going into further detail. The dealers who sold Leonardo’s Salvator Mundi feel
that Sotheby’s, which sourced a dozen of the works Bouvier sold to
Rybolovlev, should have helped them get around Bouvier so they could
make the higher sale to Rybolovlev themselves.
Here’s what the Times says is the dealer’s evidence:

Much of the speculation about Sotheby’s role in the sale
of the Leonardo revolves around what its representative knew, or didn’t
know, in 2013 when he took the “Salvator Mundi” to a Central Park
apartment, where Mr. Bouvier and Mr. Rybolovlev inspected it.

The meeting occurred six weeks before the sale to Mr.
Bouvier and the flip to Mr. Rybolovlev. The meeting took place in a
grand apartment, one of the most expensive in Manhattan, that is owned
by a Rybolovlev family trust.

In its court papers, Sotheby’s argues that its
representative, Samuel Valette, its vice chairman for private sales
worldwide, did not realize it was Mr. Rybolovlev’s family apartment or
that he was inspecting the painting as a potential buyer.

The meeting had been requested by Mr. Bouvier, the
auction house said, and though Mr. Valette said that he recognized a
third man in the room as having been associated with a previous sale to
Mr. Bouvier, he said that he had not known his name.“

It was not, however, until much later that Valette and Sotheby’s learned that this third man was Rybolovlev,” the papers state.

One of the interesting wrinkles to this story is that Central Park
West apartment. Rybolovlev bought it five years ago from Sandy Weil for
$88m in a transaction that still marvels real estate experts. It seems
that Rybolovlev’s credulous habits were not confined to his art
purchases....MORE